Load sensing technology is a technology to determine a load carried by a certain structure or a machine, or by a component thereof. The structure, machine or component is then provided with one or more load sensors. For example, the machine is an automobile and the individual loads on individual ones of the wheels are determined via the wheel hubs. The information about the loads is used to electronically control, e.g., the amount of power supplied to each driven wheel individually, or the amount of braking applied to each individual wheel, or to adjust the suspension system for each wheel individually, in order to improve the vehicle's road handling. Load sensing technology is also used in, e.g., payload weight measurements on machines such as trucks for bulk transport, warehouse trolleys, household washing machines, conveyor belts, elevators, cranes and hoisting equipment, etc. Load sensing technology is also used in condition monitoring or operational control of machines such as, e.g., wind turbines, industrial equipment, marine propulsion systems, aeronautic propulsion systems, etc.
A specific branch of load sensing technology relates to physically integrating the one or more load sensors with a rolling-element bearing. The load on the rolling element bearing causes an elastic deformation of the rolling element bearing. The deformation is sensed by one or more strain sensors accommodated at the rolling element bearing. The load is determined from the elastic deformation as sensed.
U.S. Pat. No. 7,444,888, issued to Hendrik Anne Mol and Gerrit Cornelis van Nijen, and incorporated herein by reference, discloses a method and sensor arrangement for determining a contact force vector acting on a rolling element bearing in operation. As known, a rolling element bearing comprises an inner ring, an outer ring and a plurality of rolling elements accommodated between the inner ring and the outer ring. Examples of rolling elements are balls, cylindrical rollers, needle rollers, and tapered rollers. Sensor signals are received from a plurality of sensors measuring performance characteristics of the rolling element bearing. The received sensor signals are processed to determine the contact force vector. The plurality of sensors are arranged to measure a bearing component deformation, and the step of processing comprises the step of determining the contact force vector using an inverse transformation of a finite element analysis model which describes the rolling element bearing. The finite element analysis model is simplified using at least one generalized-mode shape, the at least one generalized-mode shape being a mathematical description of a natural or elementary mode deformation of a component of the rolling element bearing, such as the inner ring or the outer ring.
The technology disclosed in U.S. Pat. No. 7,444,888 is based on measuring a deformation of the inner ring and/or of the outer ring of the rolling element bearing. The deformation is brought about by the rolling contacts between the rolling elements on the one hand, and the inner ring and/or outer ring on the other hand, while the rolling element bearing is being subjected to a load. The deformation is measured while the inner ring and the outer ring of the rolling element bearing are moving relative to each other. Each specific one of the sensors supplies a specific sensor signal indicative of the local deformation of the inner ring or of the outer ring at the location of the specific sensor. The local deformation changes dynamically as a result of the repetitive passing of rolling contact forces (also referred to as “Hertzian contact forces”).
The repetitive passing of the rolling contact forces is characterized by the ball-pass frequency. The expression “ball-pass frequency” refers to the number of rolling elements that pass the location of the sensor per unit of time. The specific sensor signal reflects this repetitive character. The amplitude of the specific sensor signal is considered proportional to the load on the rolling element bearing. Measuring the amplitude gives therefore information about the load on the rolling element bearing. For more background information see, e.g., SKF Ball Bearing Journal Vol. 225, 1985, pp 19-24 or SKF Ball Bearing Journal Vol. 240, 1992, pp 2-9.
U.S. Pat. No. 7,389,701, issued to Hendrik Anne Mol and incorporated herein by reference, discloses a method and sensor arrangement for determining a load vector acting on a rolling element bearing in operation. The expression “load vector” refers to the complete load vector: three orthogonal force components and two moments. The rolling element bearing comprises an inner ring, an outer ring and multiple rolling elements that are accommodated between the inner ring and the outer ring. A plurality of N sensors are provided, which measure displacement and/or strain for determining displacement and/or strain in, e.g., the inner ring or the outer ring. Furthermore, a mode-shape coefficients calculator is provided, connected to the plurality of N sensors, for determining a deformation of the inner ring or the outer ring by calculating amplitude and phase of N/2 Fourier terms representing at least one radial mode shape of the inner ring or the outer ring.
The technology disclosed in U.S. Pat. No. 7,389,701 considers the rolling element bearing as a physical object that deforms elastically under load. The deformation is approximated by a linear combination of generalized mode shapes. According to component mode synthesis (CMS), the generalized mode shapes can be described according to the approach discussed in J. A. Wensing, “On the dynamics of ball bearings”, PhD thesis, Univ. Twente, The Netherlands, December 1998, ISBN 90-36512298. Each respective one of the generalized mode shapes has a respective amplitude and a respective phase that are determined from the sensor signals. A data processor, a neural network or another type of associative memory, receives an input representative of the amplitudes and the phases as determined from the sensor signals, and supplies an output representative of the current load.
Accordingly, U.S. Pat. No. 7,444,888, SKF Ball Bearing Journal Vol. 225, 1985, pp 19-24, or SKF Ball Bearing Journal Vol. 240, 1992, pp 2-9, teach that the mechanical load on a rolling element bearing can be determined from the amplitude of a sensor signal that is indicative of the repetitive local deformation of the inner ring or the outer ring as a result of the rolling contacts (Hertzian contacts). The repetitive local deformation is brought about by a rolling element that is passing the location where the local deformation is being measured.
In practice, however, the amplitude of the sensor signal is somewhat different per different one of the passing rolling elements. A reason for this is the following. Consider the very high value of the hardness of the inner ring or of the outer ring in the region where they are in physical contact with the rolling elements (e.g., 100 N/μ indicating that a force of 100 N is required to create a deformation of 1μ), and also consider the miniscule spread in diameter of the rolling elements (accuracy in the order of, e.g., 5μ for a ball in a typical mass-produced ball-bearing). Accordingly, the amplitude of the sensor signal representative of the passing of a rolling element may vary by 10% among the rolling elements although the load on the rolling element bearing remains the same.
The accuracy of the magnitude of the mechanical load, as determined by the approach discussed in, e.g., U.S. Pat. No. 7,444,888, SKF Ball Bearing Journal Vol. 225, 1985, pp 19-24 or SKF Ball Bearing Journal Vol. 240, 1992, pp 2-9, can be improved by considering the amplitudes during a larger number of revolutions of the rolling element bearing in order to average out the fluctuations that are not caused by the load externally applied on the rolling element bearing. This averaging is implemented by means of, e.g., removing the DC-component from the sensor signal in order to produce a waveform, rectifying the waveform and then applying a low-pass filter to the rectified waveform so as to equalize the amplitudes to a mean value. The cut-off frequency of the low-pass filter is chosen so as to have each one of the rolling elements passing at least once the location of the deformation sensor within the characteristic time-constant of the low-pass filter. That is, the characteristic time-constant is made dependent on the speed of revolution, at which the inner ring and the outer ring of the rolling element bearing are rotating with respect to each other. For example, in a rolling element bearing whose inner ring is rotating at, say, 4 revolutions per second with respect to the outer ring, each of the rolling elements is completing its circuit around the inner ring at half that speed, i.e., every half second. The cut-off frequency of the low-pass filter is then chosen in the order of 1 Hz, so as to average over about two complete laps around the circuit. If the cut-off frequency is set to ½ Hz, the averaging is performed over about four complete laps.
Accordingly, the cut-off frequency of the low-pass filter is tuned under control of the speed of rotation of the inner ring relative to the outer ring so as to be able to achieve an accurate representative of the mechanical load on the rolling element bearing.
The accuracy of the load, as determined by considering the repetitive local deformations driven by the passing of the rolling elements, implies that variations in the actual mechanical load on the rolling element bearing with frequencies higher than the cut-off frequency are not accounted for, as these have been attenuated by the low-pass filter. For example, the suspension system of a wheeled vehicle has an eigen-frequency in the range of 2 Hz-7 Hz in order to effectively manage the typical, varying forces transmitted from the road surface to the chassis of the traveling vehicle. In above example of the 1 Hz cut-off frequency, these dynamically varying contributions to the mechanical load are not taken into account. The load determined by averaging the repetitive deformations, driven by the passing of the rolling elements, is therefore referred to in the remainder of this text as “the average contribution” to the mechanical load. The relevant contribution to the mechanical load, which is characterized by frequencies higher than the cut-off frequency of above low-pass filter, is referred to in this text as “the dynamic contribution”.
In order to determine the dynamic contribution, the approach can be used of, e.g., U.S. Pat. No. 7,389,701, discussed above. That is, the dynamic contribution is determined by considering the one or more signal components of the global deformation of the rolling element bearing that have a timescale associated with frequencies higher than the cut-off frequency of the low-pass filter discussed above.
In order to determine the dynamic contribution, the sensor signals considered in determining the global deformation need to be filtered so as to remove the signal components that have already been taken into account in the determining of the average contribution. Accordingly, a high-pass filter is needed with a cut-off frequency that, for all practical purposes, equals the cut-off frequency of the low-pass filter used in the determining of the average contribution. This ensures that the average contribution to the load and the dynamic contribution to the load, in a frequency range which contains the common cut-off frequency, can be summed without introducing severe errors as a result of duplicating or omitting contributions falling within this frequency range. The high-pass filtering also removes the contributions to a global deformation of the rolling element bearing that are driven by thermal effects, such as caused by friction, as thermal effects have a characteristic timescale of many seconds. Also, the sensor signals considered in determining the global deformation need to be filtered so as to remove the signal components with frequencies in the order of the ball-pass frequency and above. Accordingly, a further low-pass filter is applied that has a cut-off frequency higher than the cut-off frequency of the high-pass filter but lower than the ball-pass frequency, in order to remove the latter signal components. The cut-off frequency of the further low-pass filter is taken as, e.g., 10 Hz in above example relating to the suspension system of the wheeled vehicle. The local elastic deformations occurring at the ball-pass frequency as a result of the passing of the rolling elements are considered a disturbance superimposed on the global elastic deformation. In above example, the global deformation is calculated using the deformation components in the frequency range between 1 Hz and 10 Hz. The local deformation caused by the passing of the rolling elements is picked-up via the carrier frequency (i.e., the ball-pass frequency) and demodulated with a bandwidth of 1 Hz. The system designer now has to find an acceptable compromise between the desired filter properties and the desired error rejection rate. The sharper a filter is, the more ringing is found. As known, removing the high-frequency components from a signal causes undesired oscillations (“ringing”) in the time-domain as a result of the ripples in the sinc-function being the time domain response of a perfect low-pass filter to a step function. A compromise is, for example, to use a second-order or a fourth-order Butterworth filter. One could also use an approach disclosed in U.S. Pat. No. 5,698,788 issued to Hendrik Anne Mol and Cornelis van Nijen, and assigned to SKF. U.S. Pat. No. 5,698,788 discloses a method for analyzing regularly recurring mechanical vibrations. The method comprises the steps of plotting an amplitude/time spectrum associated with the vibrations, dividing the amplitude/time spectrum into time intervals shorter than the shortest time lapse between two consecutive excitations, subjecting those parts of the amplitude/time spectrum defined by each time interval to a Fourier transformation in order to obtain an amplitude/vibration-frequency interval spectrum associated with each time interval, and subjecting those amplitudes in each amplitude/vibration frequency interval spectrum associated with certain vibration frequencies to a Fourier transformation in order to obtain an excitation-frequency spectrum associated with the respective vibration frequency. Effectively, the high-pass filter and the further low-pass filter form a band-pass filter.
The idea is therefore the following. The DC-component is removed from the one or more sensor signals used for determining the average contribution to the load, using as input the amplitude of the local deformation driven by the rolling contact forces. The remaining AC-components are rectified and then averaged in a low-pass filter before being further processed to determine the average contribution to the load. The sensor signals, used for determining the dynamic contribution to the load using the global deformation, are subjected to a band-pass filter before being further processed. The cut-off frequency of the low-pass filter and the lower one of the cut-off frequencies of the band-pass filter are set to be substantially equal. The cut-off frequencies of the low-pass filter and of the band-pass filter are controlled in dependence on the speed of revolution of the inner ring and the outer ring of the rolling element bearing relative to one another. The load is then determined as the sum of the average contribution and the dynamic contribution.